Over the past few years, generative models have gained the ability to generate images with high visual quality. A few of the most widely used methods include generative adversarial networks (GANs) [1]}, VAE [2]}, invertible neural networks [3]}, [4]}, and diffusion models [5]}, [6]}. In particular, generative models trained on large amounts of unlabeled data, e.g., BigGAN [7]}, StyleGANs [8]}, [9]}, [10]}, [11]}, Glow [12]}, and diffusion models [13]}, [14]}, achieve promising image synthesis results.
